Heliyon (Dec 2023)

A systematic review and meta-analysis on ChatGPT and its utilization in medical and dental research

  • Hiroj Bagde,
  • Ashwini Dhopte,
  • Mohammad Khursheed Alam,
  • Rehana Basri

Journal volume & issue
Vol. 9, no. 12
p. e23050

Abstract

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Background: Since its release, ChatGPT has taken the world by storm with its utilization in various fields of life. This review's main goal was to offer a thorough and fact-based evaluation of ChatGPT's potential as a tool for medical and dental research, which could direct subsequent research and influence clinical practices. Methods: Different online databases were scoured for relevant articles that were in accordance with the study objectives. A team of reviewers was assembled to devise a proper methodological framework for inclusion of articles and meta-analysis. Results: 11 descriptive studies were considered for this review that evaluated the accuracy of ChatGPT in answering medical queries related to different domains such as systematic reviews, cancer, liver diseases, diagnostic imaging, education, and COVID-19 vaccination. The studies reported different accuracy ranges, from 18.3 % to 100 %, across various datasets and specialties. The meta-analysis showed an odds ratio (OR) of 2.25 and a relative risk (RR) of 1.47 with a 95 % confidence interval (CI), indicating that the accuracy of ChatGPT in providing correct responses was significantly higher compared to the total responses for queries. However, significant heterogeneity was present among the studies, suggesting considerable variability in the effect sizes across the included studies. Conclusion: The observations indicate that ChatGPT has the ability to provide appropriate solutions to questions in the medical and dentistry areas, but researchers and doctors should cautiously assess its responses because they might not always be dependable. Overall, the importance of this study rests in shedding light on ChatGPT's accuracy in the medical and dentistry fields and emphasizing the need for additional investigation to enhance its performance.© 2017 Elsevier Inc. All rights reserved.

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